Senior Software Engineer, Distributed Systems Engineer - DGX Cloud at NVIDIA

Austin, Texas, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Technology, Cloud ComputingIndustries

Requirements

Direct experience in a software engineering role within a highly technical organization with demonstrable impact
Software development experience with Kubernetes APIs and frameworks (not just operating a cluster)
Significant software engineering experience with Kubernetes, including cluster operations, operator development, node health monitoring, and GPU resource scheduling
8+ years in a similar role with experience on large-scale production systems
Experience with common software engineering principles, tools, and techniques
BS in Computer Science, Engineering, Physics, Mathematics, or comparable degree (or equivalent experience)
Technical knowledge, including a systems programming language (Go, Python) and solid understanding of data structures and algorithms
Highly motivated with strong communication skills; ability to work with multi-functional teams, principals, architects, and coordinate across organizational boundaries and geographies

Responsibilities

Work on custom software related to scheduling GPU resources on Kubernetes as part of the DGX Cloud team for production systems enabling large scalable GPU clusters for AI workloads
Implement monitoring and health management capabilities for industry-leading reliability, availability, and scalability of GPU assets, harnessing data streams from GPU hardware diagnostics to cluster and network telemetry
Collaborate with teams across NVIDIA to ensure production AI clusters run reliably and consistently with maximum performance
Evaluate system failures and improve services based on a well-defined incident management process

Skills

Key technologies and capabilities for this role

KubernetesCluster OperationsOperator DevelopmentNode Health MonitoringGPU Resource SchedulingGPU Hardware DiagnosticsCluster TelemetryNetwork TelemetryIncident ManagementDistributed Systems

Questions & Answers

Common questions about this position

What experience is required for this Senior Software Engineer role?

Candidates need 8+ years in a similar role with experience on large-scale production systems, direct software engineering experience with Kubernetes APIs and frameworks (beyond just operating clusters), and technical knowledge including a systems programming language like Go or Python plus understanding of data structures and algorithms.

What is the salary or compensation for this position?

This information is not specified in the job description.

Is this a remote position or does it require office work?

This information is not specified in the job description.

What is the company culture like at NVIDIA for this team?

The role involves constant challenges to improve and evolve, working with out-of-the-box thinkers who provide new ideas with strong execution, and collaborating across multi-functional teams, principals, architects, organizational boundaries, and geographies in a highly motivated environment.

What makes a candidate stand out for this DGX Cloud engineer role?

Stand out with technical competency in managing and automating large-scale distributed systems independent of cloud providers, plus advanced hands-on experience and deep understanding of Kubernetes including cluster operations, operator development, node health monitoring, and GPU resource scheduling.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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